Spectrometric investigation of heterogeneity

ABSTRACT

In one general aspect, a spectroscopic apparatus is disclosed for investigating heterogeneity of a sample area. The apparatus includes an image acquisition system operative to acquire images of a plurality of sub-areas in the sample area and a sub-area selection interface operative to receive a selection designating one of the sub-areas for which an image has been obtained. A spectrometer has a field of view and is operative to acquire a spectrum of at least part of one of the sub-areas in its field of view, and a positioning mechanism is responsive to the sub-area selection interface and operative to position the field of view of the spectrometer relative to the sample area based on a received selection.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. 119(e) of UnitedStates provisional application entitled SPECTROMETRIC INVESTIGATION OFHETEROGENEITY, filed Jan. 5, 2007 (Ser. No. 60/879,306), and UnitedStates provisional application entitled SPECTROMETRIC INVESTIGATION OFPHARMACEUTICAL HETEROGENEITY, filed Jul. 5, 2007 (Ser. No. 60/958,337),both of which are herein incorporated by reference.

FIELD OF THE INVENTION

This invention pertains to instrumentation, including particle imageanalyzers with spectrometric capabilities.

BACKGROUND OF THE INVENTION

Particle image analyzers are well-known instruments that can use imageanalysis techniques to allow users to automatically acquire and analyzeimages of a large number of particles. These instruments can thenprovide statistical information about the size and shape of particles.FIG. 1 shows one example of such a system, the Morphologi® ParticleImage Analyzer available from Malvern Instruments, Inc. of Malvern UK.This system is described in a section of the specification of thisdocument.

Spectral imaging techniques have also been applied to the analysis oflarge numbers of particles. These systems can provide statisticalinformation about the distribution of chemical species in the particles.Systems of this type are described in more detail in US publishedapplication no 20060282223, which is herein incorporated by reference.

SUMMARY OF THE INVENTION

Several aspects of the invention are presented in this application. Inone general aspect, the invention features a spectroscopic apparatus forinvestigating heterogeneity of a sample area. The apparatus includes animage acquisition system operative to acquire images of a plurality ofsub-areas in the sample area and a sub-area selection interfaceoperative to receive a selection designating one of the sub-areas forwhich an image has been obtained. A spectrometer has a field of view andis operative to acquire a spectrum of at least part of one of thesub-areas in its field of view, and a positioning mechanism isresponsive to the sub-area selection interface and operative to positionthe field of view of the spectrometer relative to the sample area basedon a received selection.

In preferred embodiments, the positioning mechanism can includeelectromechanical elements. The positioning mechanism can include an x-ystage responsive to x-y coordinate information from the sub-areaselection interface. The sub-area selection interface can be responsiveto direct selection of a sub-area by a user. The apparatus can furtherinclude analysis logic operative to analyze the images acquired by theimage acquisition system. The sub-area selection interface can beresponsive to the analysis logic to select sub-areas havingpredetermined characteristics. The sub-area selection interface can beresponsive to the analysis logic to select sub-areas havingpredetermined morphological characteristics. The sub-area selectioninterface can be responsive to the analysis logic to select sub-areashaving predetermined color characteristics. The analysis logic caninclude statistical analysis logic, sorting logic, and/or contaminantdetection logic. The spectrometer can be an infrared spectrometer. Thespectrometer can be a Raman spectrometer. The area can be an area ofdispersed particles with the sub-areas being individual particles in thearea of dispersed particles. The image acquisition system can operate inthe visible range. The apparatus can further include a mapping moduleresponsive to the image acquisition system and to the spectrometer andoperative to create a map that presents spectral information for each ofthe sub-areas from the spectrometer at a location from which it wasreceived. The mapping module can be operative to superimpose thespectral information onto an image from the image acquisition system.The mapping module can map point measurement values to larger areashaving matching physical characteristics. The mapping module can also beoperative to indicate statistical properties of mapped areas.

In another general aspect, the invention features a spectroscopic methodfor investigating heterogeneity of a sample area that includes acquiringimages of a plurality of sub-areas in the sample area using an imageacquisition system, receiving a selection of one of the sub-areas forwhich an image has been obtained, positioning a field of view of aspectrometer relative to the sample area so as to place at least part ofthe selected sub-area in the field of view, and acquiring a spectrum ofthe selected sub-area.

In preferred embodiments, the method can further include the step ofmapping spectral information from the spectrometer to a location fromwhich it was received. The method can further include the steps ofderiving physical information about the one of the sub-areas, andsetting a spectral range of the step of acquiring in response to thephysical information.

In a further general aspect, the invention features a spectroscopicapparatus for investigating heterogeneity of a sample area that includesmeans for acquiring images of a plurality of sub-areas in a sample,means for receiving a selection of one of the sub-areas for which animage has been obtained, means for positioning a field of view of aspectrometer relative to the sample area so as to place at least part ofthe selected sub-area in the field of view, and means for acquiring aspectrum of the selected sub-area.

In another general aspect, the invention features a spectroscopic methodfor investigating heterogeneity of a sample area that includes receivingspatial information for a plurality of sub-areas in a sample area,receiving separate spectral information items for each of the pluralityof sub areas, wherein a selection of the separate spectral informationitems is based on the spatial information, and combining the spatialinformation with the spectral information to create a map showingspatial distribution of spectral information for the sample area.

In preferred embodiments, the method can further include the step ofacquiring the spatial information by a preliminary imaging system andthe step of acquiring the spectral information by a spectrometer that isresponsive to automatically generated identification information derivedfrom the spatial information acquired in the step of acquiring.

In a further general aspect, the invention features a spectroscopicapparatus for investigating heterogeneity of a sample area that includesmeans for receiving spatial information for a plurality of sub-areas ina sample area, means for receiving separate spectral information itemsfor each of the plurality of sub areas, wherein a selection of theseparate spectral information items is based on the spatial information,and means for combining the spatial information with the spectralinformation to create a map showing spatial distribution of spectralinformation for the sample area.

In another general aspect, the invention features an apparatus forinvestigating heterogeneity of a sample area that includes an imageacquisition system operative to acquire images of a plurality ofsub-areas in the sample area, a sub-area selection interface operativeto automatically select one of the sub-areas for which an image has beenobtained based on its color, and quantitative analysis logic operativeto perform a quantitative analysis on image data from one or more of thesub-areas. In preferred embodiments, the sub-area selection interfacecan be operative to automatically select one of the sub-areas for whichan image has been obtained based on a color that corresponds to apredetermined stain.

In a further general aspect, the invention features a method forinvestigating heterogeneity of a sample area that includes acquiringimages of a plurality of sub-areas in the sample area, automaticallyselecting one of the sub-areas for which an image has been obtainedbased on its color, and performing a quantitative analysis on image datafrom one or more of the sub-areas.

In another general aspect, the invention features an apparatus forinvestigating heterogeneity of a sample area that includes means foracquiring images of a plurality of sub-areas in the sample area, meansfor automatically selecting one of the sub-areas for which an image hasbeen obtained based on its color, and means for performing aquantitative analysis on image data from one or more of the sub-areas.

Systems according to the invention can be advantageous in that theyallow for spectrometric imaging and screening without the expense andtime that may be required by array-based infrared chemical imagingsystems.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an image of a prior art particle image analyzer;

FIG. 2 is an image of a system according to the invention employing theanalyzer of FIG. 1;

FIG. 3A is an illustration of a screen shot particle record view thatcan be provided by the system of FIG. 2 for a first type of particle inan illustrative sample;

FIG. 3B is a spectrum for one of the particles shown in the screen shotof FIG. 3A, which can be provided by the system of FIG. 2;

FIG. 4A is an illustration of a screen shot particle record view thatcan be provided by the system of FIG. 2 for a second type of particle inan illustrative sample;

FIG. 4B is a spectrum for one of the particles shown in the screen shotof FIG. 4A, which can be provided by the system of FIG. 2;

FIG. 5 is a series of images illustrating a sequence of screen shotsthat can be produced by the system of FIG. 2 for an illustrative sample;

FIG. 6A is a series of selected images of samples from an illustrativesample for use with the system of FIG. 2;

FIG. 6B is a graph illustrating the intensity distribution oftransparency in the illustrative sample for FIG. 6A;

FIG. 6C is a plot showing a family of spectra for different types ofsamples in the illustrative sample;

FIG. 7 is a block diagram of a system according to the invention thatemploys a sparse image information acquisition mode;

FIG. 8 is an acquired grayscale image of a pharmaceutical formulationwith two active ingredients and one inactive ingredient dispersed onto asurface using a standard metered-dose inhaler;

FIG. 9 is a diagram illustrating a blank hypercube data set for theimage of FIG. 7;

FIG. 10A is a diagram illustrating a populated sparse hypercube data setthat employs image areas that each correspond an individual spectrum;

FIG. 10B is a diagram illustrating a populated sparse hypercube data setthat employs image areas that each correspond to a plurality of spectra;

FIG. 11 is a map of the type that can be produced with a system such asthe system of FIG. 7 based on the sample for which an acquired image isshown in FIG. 8.

FIGS. 12-20 illustrate a particle analyzer.

DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT

Referring to FIG. 2, an illustrative system 10 according to theinvention includes a spectrometer 22 in addition to the microscope body12, x-y stage 14, and camera 16. The spectrometer can use the samemicroscope optics as the camera either by swapping them or using anoptical switch to alternate between them. In Raman implementations, alaser source can also pass its beam through the same optics, such asthrough the use of a beam splitter 24.

Results from the camera and computer are also preferably analyzed andpresented on a same computer (e.g., a PC workstation). The principles ofthe invention can be applied to a variety of types of apparatuses,methods, and applications. For example, a system employing macroscopicoptics could be used instead of microscopic optics. The camera couldacquire its images in a variety of ways, such as by using a ChargeCoupled Device (CCD) to acquire grayscale or color images in the visiblewavelength range. These apparatuses can also employ any type ofspectrometric detection, such as methods based on gratings orinterference. And while the illustrative embodiment uses NIRspectrometry, other types of spectrometry could be used as well, such asmid-infrared spectrometry, Raman spectrometry, or fluorescencespectrometry.

In operation, referring to FIG. 3A, the system first acquires a visibleimage of a sample area, such as a dry dispersion of particles from apharmaceutical raw material. The system can then provide the user aseries of images of individual particles. This can allow the user toselect one of the particles and then cause the system to obtain aspectrum of that particle by moving the x-y to position the selectedparticle in a field of view of the spectrometer (see FIG. 3B). Note thatother types of mechanisms for moving the sample relative to thespectrometer's field of view are possible, such as by moving mirrors, oreven moving the spectrometer itself. Some can also operate passively,such as by gravity or convection. The field of view of the spectrometeris preferably smaller than the size of a particle.

The system can also select particles automatically. Results ofstatistical or other types of image or numerical analysis can be used todetermine which particles to select based on morphological differences.For example, the smallest, largest, most spherical, darkest, or lightestparticles could be selected automatically (e.g., compare FIGS. 3A and 3Bwith FIGS. 4A and 4B). Combinations of morphological, physical,calorimetric, or other attributes could be used as well.

The system can also be applied to other types of samples, such as coarseor fine particulates and heterogeneous liquids or surfaces. Morespecific examples can include items such as manufactured products,seeds, cattle feed, biological cells or other bounded biologicalentities such as spores, organelles, or bacteria. Other types ofoperations can also be applied to selected areas by the system. Aparticle could be mechanically extracted for disposal or furtherprocessing, for example.

Referring to FIGS. 5-6, in one example, particles having differenttransparencies could be processed by the system. In this example, mostparticles are semi-transparent and produce low intensity images, whilesome are darker and result in higher contrast images (see FIG. 6A). Asshown in FIG. 6B, statistical processing by the system can reveal thatthe transparency distribution for this sample has two peaks-one largeone for the most common, more transparent, particles and one small onefor the less common, darker, particles. The system can then produce oneor more spectra for a variety of salient points in this distribution,such as at the centroids of its peaks or their outlying edges (see FIG.6C). These spectra can then be displayed to the user or compared toknown spectra in a spectral library or processed by a variety ofmultivariate or chemometrics means. These processing operations canderive information about the chemical origin or identification of theselected object or more fundamental information about the molecular orcrystal structure.

Referring to FIGS. 7-8, systems according to the invention can also usea sparse image information acquisition and/or mapping mode. In thismode, the system can obtain a first image of a sample area in whichinformation of interest is relatively sparse. This image may include asparse set of entities of interest separated by background space, suchas the dispersed pharmaceutical formulation shown in FIG. 8, or it mayinclude any other type of image in which only a small number of imagesub-areas are of interest.

Referring to FIG. 9, one traditional prior art method of acquiringspectral information for a sample area is to acquire a full spectrum forevery point to derive a full spectral hyperspectral data cube for thesample. This data cube includes an x-y image of the sample at each of aseries of wavelengths λ, with a vector v in the wavelength axiscorresponding to a single point spectrum. Much effort has been expendedto build high-speed imaging spectrometers that can create fullhyperspectral data cubes quickly.

Systems according to the invention operate differently. These systemsfirst employ a preliminary imaging detection subsystem to selectparticles of interest. This step can be automatic or semi-automatic, andcan be based on a variety of information about the sample, such asmorphology, colorimetry, statistical properties, or pattern recognition.It is also preferably quick and/or inexpensive to perform, because itoperates at visible wavelengths, for example. The particles selected bythe preliminary imaging subsystem are identified to a spectrometrysystem, such as in the form of a list of particle centroids communicatedelectronically.

As in the embodiment presented above in connection with FIG. 2, thesystem can cause the spectrometer to obtain one or more spectra for eachof the particles of interest by moving the position of an x-y stage tothe selected particles in a field of view of the spectrometer. Note thatother types of mechanisms for moving the sample relative to thespectrometer's field of view are also possible, such as by movingmirrors, or even moving the spectrometer itself. Some can even operatepassively, such as by gravity or convection.

Referring to FIGS. 10A-10B, the values from the spectrometer are mappedto locations in a sparse hyperspectral data cube that correspond to therespective locations of sub-areas of interest, such as particles. Thismapping can take a variety of forms, such a single-sample, geometricmap, in which each sub-area is represented by a geometrically accuratesub-area shape exhibiting a single representational treatment (e.g., acolor or a hatching pattern). Each shape in this type of map correspondsto a single spectral measurement of a single particle, such as one takenat its centroid (see FIG. 10A). And each shape has a perimeter thatmatches the perimeter of its respective particle and is located in theimage at a location that corresponds to its location in the sample area.The result is a map that can resemble a map derived from a full spectralscan of the sample area, but includes little or no data outside theregions of interest. In the case of the pharmaceutical formulation, forexample, the different types of particles in the formulation could bemapped to different colors on a white background. Or they could bemapped to different hatching patterns, as shown in FIG. 11.

A multi-sample, geometric map can be used as well, in which eachsub-area is actually a small spectral image of the sample with aplurality of pixels each corresponding to one of several differentlylocated spectral measurements for different parts of the sub-area.Multi-sample maps can also display a single treatment for each sub-area,where the treatment is defined by the results of multiple samples (seeFIG. 10B). For example, a median wavelength response for a series ofmeasurements taken over different parts of a sub-area could be computedand displayed as a color. Suitable techniques used for obtainingmultiple samples for a sub-area, including statistical techniques, aredescribed, for example, in copending application no. 60/860,345,entitled SPECTROMETRIC CHARACTERIZATION OF PHARMACEUTICAL HETEROGENEITY,filed on Nov. 20, 2006, which is herein incorporated by reference.

The system can produce maps in a variety of ways. It may produce them bysuperimposing results from the spectrometer onto the image produced bythe preliminary imaging system, for example, or it may produce themusing the results of the preliminary imaging system as a starting pointfor a mask. They maps can also be produced based only on the locationand/or morphology information received from the preliminary imagingsystem.

The data sets can be stored in a variety of ways. They can be stored inmuch the same way would be a full hyperspectral data cube, except thatnon-sampled areas would be represented as empty, such as through the useof an IEEE 754 floating point NaN symbol (Not a Number). They can alsobe stored in a more compact format to reduce data storage requirements.This format could include a data structure that holds the receivedspectra and their coordinates, for example, or it could employ one ofmore of a variety of known data compression methods suitable forencoding sparse data sets, such as Run Length Encoding (RLE). To displaya map or image plane from a compactly stored data cube, the system wouldhave to decompress or otherwise reconstruct the map or image.

The maps and data sets may also be spatially compressed. If eachsub-area only corresponds to a single measurement, for example, the datacould be presented and stored at a much lower resolution that that ofthe preliminary imaging system. And in some applications, it may besuitable to represent each sub-area with a representation that does notconform to the shape of the sub-areas, such as an individual pixel, oreven a symbol. All of the above techniques can permit faster acquisitiontimes, processing times, and/or storage requirements by reducingredundant or unimportant operations and/or spatial data.

The data sets, maps, and spectral measurements may also exhibit spectralsparseness. The selections presented by the preliminary imaging systemcan define which wavelengths should be used for different sub-areas of asample area, for example, such as by adjusting an excitation frequency(e.g., selecting a laser frequency) or selecting a sensitivity range forthe spectrometer. This approach can further reduce acquisition times,processing times, and/or storage requirements by reducing redundant orunimportant operations and/or spectral data. Once maps have beencreated, they can be displayed, stored, or serve as the basis forfurther investigation or processing.

Systems according to the invention can be created using a speciallyprogrammed general purpose computer, dedicated hardware, or acombination of both. In one embodiment, the system is based on aMicrosoft Windows®-based computer system, but other platforms could beused as well.

Techniques presented in this application such as the sparse acquisitiontechniques can also be applied to high throughput systems, such as aredescribed in U.S. Pat. No. 6,483,112, entitled HIGH-THROUGHPUT INFRAREDSPECTROSCOPY. They may also be applied to high-volume on-linespectroscopic composition testing of manufactured pharmaceutical dosageunits such as are described in U.S. Pat. No. 6,690,464, entitledHIGH-VOLUME ON-LINE SPECTROSCOPIC COMPOSITION TESTING OF MANUFACTUREDPHARMACEUTICAL DOSAGE UNITS. And they may be applied to HPLC and othertechniques described in U.S. application Ser. No. 10/328,713, entitledSPECTROMETRIC PROCESS MONITORING. All of these applications are hereinincorporated by reference.

In addition to combining the teachings of this application with theabove-referenced documents, it is contemplated that they could also becombined with the teachings of U.S. application Ser. No. 11/499,390,entitled PHARMACEUTICAL MIXTURE EVALUATION, filed on Aug. 4, 2006, U.S.application No. 60/860,345, entitled SPECTROMETRIC CHARACTERIZATION OFPHARMACEUTICAL HETEROGENEITY, filed on Nov. 20, 2006, and U.S.application No. 60/879,306, entitled SPECTROMETRIC INVESTIGATION OFHETEROGENEITY, filed on Jan. 5, 2007. For example, particles could bestained before image acquisition and analysis, and color resulting fromstaining could be used as a selection parameter. All of theseapplications are herein incorporated by reference.

Particle Analyzer

The following section describes a particle analyzer suitable for use inconnection with embodiments of the invention. This analyzer is soldunder the name “Morpohologi G2” by Malvern Instruments Limited ofMalvern, Worcestershire UK. Referring to FIG. 12, the Morphologi G2 highsensitivity particle analyzer is more than just a microscope. It bringstogether the very best hardware and software in a single integratedpackage and provides the very highest level of automation and validationof results. It provides repeatable and routine characterization ofparticle size, shape and count.

The Morphologi G2 is equipped with the renowned Nikon CFI 60 opticalsystem coupled with a high resolution digital camera for high definitionaberration-free images. Microscope-quality images and statisticallysignificant histograms offer both qualitative and quantitativeinformation which can eliminate operator bias and saves preciousman-hours. In R&D, process analysis or quality control, the MorphologiG2 delivers reliable, repeatable and validated results in minutes. Itcan analyze 100s of thousands of particles at the push of a button,provide particle shape and count as well as size information, recordhigh resolution images of every particle, automatically select optics,focus and light intensity control, provide technical compliance with 21CFR Part 11, and provide a dedicated sample preparation device. Usage ofthe system is illustrated Table 1, with reference to FIGS. 13-17.

TABLE 1 Step Description Comments FIG. Method Generate basic A “manualmicroscope” mode 13 Development information on sample is available toquickly move such as size range. around and view the sample in Optimizesample order to check basics such a dispersion conditions. dispersionquality or the approximate size rage. It employs a virtual joystick andfocus, light and magnification controls. Standard Optimize and selectall A “wizard” assists in the 14 Operating software and hardwaregeneration of SOPs. A mouse- Procedure variables. controlled scan areaselection (SOP) All variables captured tool is available. Creation in asingle file that can be emailed around the world. Sample The softwareselects During data acquisition, status 15 Measurement the magnificationand messages keep the operator calibrates against a informed ofprogress. A grating. settings icon allows for Light intensity andmodification of SOP settings. focus position are all Quick start iconand status controlled by software. message bar are also provided alongwith a live view of the measurement frame. Result View information onImages of all particles are 16 Viewing/editing each individual particlerecorded and can be sorted and or the statistics of whole filtered onany shape parameter distribution and new records created with Sort andfilter particles the filtered data. Particles can and create new recordsbe sorted and filtered on any with certain particles parameter. Asidebar shows a excluded. morphological parameter list for a highlightedparticle. Report Display distribution, A range of reports is supplied to17 Creation tables and result display distribution, tables andstatistics. results statistics. The Report Report Designer can Designercan be used to be used to customize the customize the contents of thesestyle and content of reports. Any morphological reports. parameter canbe plotted on the x-axis. The user can choose frequency, undersize, oroversize graph types, and can add specific parameters or logos or othergraphics.

Why is Shape Analysis Important? Manual microscopy and traditionalparticle sizing techniques are often not sufficiently sensitive todistinguish subtle differences in raw materials. Batches of samples maydiffer by such a small amount that this difference is lost during thetranslation to a circle-equivalent or spherical-equivalent diameter.Calculating shape parameters like the ones shown in Table 2 below alloweven the most subtle differences to be identified and quantified (seeFIG. 18).

TABLE 2 Example Parameter value Definition ID 516 Unique ID of theparticle - allocated in the order that the particles are detectedMagnification 2.50 Magnification used to make the measurement CEdiameter 904.14 The diameter of a circle with the same area as the (μm)particle Length (μm) 1306.35 All possible lines from one point of theperimeter to another point on the perimeter are projected on the majoraxis (axis of minimum rotational energy). The maximum length of theseprojections is the length of the object. Width (μm) 678.54 All possiblelines from one point of the perimeter to another point on the perimeterare projected on the minor axis. The maximum length of these projectionsis the width of the object. Max. Distance 1318.07 Largest distancebetween any two pixels in particle (μm) Perimeter (μm) 3619.42 Actualperimeter of particle Major axis° 105.52 Axis of minimum rotationalenergy Area (μm²) 371550.78 Actual area of particle in sq. microns Area(pixels) 215018 Number of pixels in particle Circularity 0.785Circumference of equivalent area circle divided by the actual perimeterof the particle = 2√ (πArea)/ Perimeter HS Circularity 0.616 Highsensitivity circularity (circularity squared) = 4πArea/ perimeter²Convexity 0.919 Convex hull perimeter divided by actual particleperimeter Solidity 0.905 Actual particle area divided by convex hullarea Aspect ratio 0.519 Width divided by length Elongation 0.461 1 -aspect ratio Intensity mean 61.310 Average of all the greyscale valuesof every pixel in the particle Intensity 29.841 Standard deviation ofall the greyscale values of every standard pixel in the particledeviation Center x position 6898271.5 x co-ordinate of center of mass ofparticle (μm) Center y position 1797186.3 y coordinate of center of massof particle (μm)

Referring to FIG. 19, shape parameters such as Circularity, Convexityand Elongation provide the user with a series of highly sensitive toolsin order to identify and quantify subtle variations in particle shapeand provide a “fingerprint” of each sample. Each parameter is usuallynormalized between 0 and 1 in order to provide quick and easycomparability. Traditional qualitative human descriptions such as“jagged”, “smooth” or “needlelike” can be accurately quantified andhence correlated against important process or end-product variables suchas flowability, active area and grinding efficiency.

Circularity is a measure of the closeness to a perfect circle.Circularity is sensitive to both changes in overall form and surfaceroughness. Convexity is a measure of the surface roughness of aparticle. Convexity is sensitive to changes in surface roughness but notoverall form. Elongation is a measure of the length-width relationship.Elongation is unaffected by surface roughness—a smooth ellipse has asimilar elongation as a apiky ellipse of smaller aspect ratio.

The Morphologi G2 includes high quality hardware to provide high qualityimages. It includes a high-resolution digital camera, and a motorizedobjective revolver that provides automatic magnification change over. Italso includes a precision XY stage for sample scanning, a motorized Zaxis actuator for automatic focusing, and two light sources forreflected (episcopic) and transmitted (diascopic) illumination. Thesystem is supplied with two flat screen monitors, one for software andthe other for a live video view. A range of sample holders are availableto suit different samples and different sample preparation types.

The Morphologi G2 is built upon the acclaimed Nikon CFI 60 opticalsystem which achieves both higher Numerical Apertures (NA) and longerworking distances. A precision XY stage and calibration grating ensurethat data is precise, secure and validated at all times. In theserevolutionary optics, both axial and lateral chromatic aberration havebeen corrected independently in the objective and the tube lens. Thisgeometry produces images that are crisp and clear with high contrast andminimal flare.

The precision engineered XY stage uses high accuracy, ground ball-screwsto provide smooth and maintenance free motion with zero-backlash. Thequiet and precise stepper motors ensure accurate positioning of thestage while the use of micro-stepping provides smooth motion at lowspeeds.

Precision etched chrome-on-glass gratings are built into the XY stagefor calibration purposes. The gratings are certified and traceable tothe National Physical Laboratory. The system automatically calibratesbefore every measurement to guarantee validated, secure data.

Morphologi G2 delivers the benefits listed in Table 3.

TABLE 3 Objectives Features Repeatability and The tried and tested SOP(Standard Operating Procedure) automation methodology records allsoftware and hardware variables in a single file. At the click of amouse the system selects and calibrates the required magnification, thelight intensity and focus before scanning a defined area. Sensitivity toParticles are fully characterized by morphological parameters includingshape circle equivalent diameter, circularity and convexity. This highquality information can be used to distinguish between materials thatappear identical to a conventional microscope or traditional particlesizer. High quality Nikon's acclaimed CFI60 optics offer longer workingdistances and high optics N.A.s and allow high contrast imaging with aminimum of flare. Statistical Large numbers of particles (typically5,000-500,000) are captured and significance analyzed in minutes or evenseconds. Images you can All images are saved for future referenceincluding the x-y coordinates see of each particle. If desired, one canprecisely move the camera back to any position for a more detailedvisual analysis. Controlled To avoid errors due to random orientation,particles are dispersed onto a orientation flat glass plate. Thisachieves consistency of orientation with the largest area facing thecamera. Regulatory The Morphologi G2 has a full validation documentationpackage compliance available and provides technical compliance with therequirements of 21 CFR part 11.

At any point in a manufacturing process from early research anddevelopment, through process-analysis, manufacturing trouble-shootingand root-cause analysis to final product quality control, thisinstrument provides an unprecedented level of product and processunderstanding. It is suitable for use in a number of areas.

The Morphologi G2 can be used for pharmaceuticals. In this application,even subtle differences in particle size or shape can significantlyaffect bioavailability, flowability, stability, blending and tablettingefficiency. Manufacturing processing steps including crystallization,drying, milling, blending, filtering can all introduce variability intothe product and have to be precisely controlled. The extra sensitivityand resolution available in the Morphologi G2 instrument provides userswith the ability to identify, measure and monitor those processvariables which are critical to product quality.

The Morphologi G2 provides high sensitivity to fine particles. Imageanalysis proceeds on a ‘number-basis’ where the contribution eachparticle makes to the distribution is the same—a very small particle hasexactly the same weighting as a very large particle. For diagnostic ortrouble-shooting purposes the presence of fines could be critical tounderstand any given manufacturing process (see FIG. 20).

The Morphologi G2 is also suitable for use in foreign particledetection. Image analysis is an ideal technology for detecting thepresence of very small numbers of foreign particles or confirmingphenomena such as agglomeration. Using single parameters or combinationsof parameters, foreign particles can be detected and quantified. Forexample, needles or fibers can be detected using the circularity shapedescriptor.

An overview of the Morphologi G2 system specifications is presented intable 4 below.

TABLE 4 Size, shape and count measurement of particulate samples Sizemeasurement Size range 0.5 μm-1000 μm (depending upon materialproperties and dispersion conditions) Shape measurement Multiple shapeparameters calculated for each particle and distribution generated oneach parameter. Parameters include: circle equivalent diameter, Length,Width, Perimeter, Area, Aspect ratio, Circularity, Convexity, Solidity,Elongation, Intensity. Optical configurations Optical system Nikon CFI60 Brightfield/Darkfield system Magnification (at camera)  2.5X  5X  10X 20X  50X Approx. total magnification 120X 240X 480X 960X 2400X (at 17″screen) Min particle size (μm) 20 10 5 3 0.5 Max particle size (μm) 1000430 210 100 40 Numerical aperture 0.075 0.15 0.30 0.40 0.55 Focal depth(total) (μm) 97.78 24.44 6.11 3.44 1.82 Working distance (mm) 8.80 18.0015.00 13.00 9.80 Camera system Camera type 1/1/8″ Global shutterprogressive scan CCD Connection protocol type IEEE 1 394a (Firewire ™)Number of pixels 1624 × 1236 (2 MegaPixel) Pixel size 4.4 μm × 4.4 μmSensor size 7.15 mm × 5.44 mm Minimum PC specification DELL Mini TowerPC, Windows XP SP2, 3.0 GHz Intel (Supplied with system) Pentium IVProcessor, 1 Gb RAM, 160 Gb-HDD, DVD +/− R/RW, complete with mouse,keyboard and 2 × 17″ Flat Panel Monitors (1 for software and 1 for livevideo feed) Weight and dimensions Weight (with stage fitted) 50 kgOverall dimensions 550(w) × 850(d) × 680(h) mm (with stage fitted)Suggested deskspace 850(d) × 2500(w) (with PC and 2 screens) Siterequirements Power requirements AC 100-240 V, 50-60 Hz Ambient operatingtemp. 10° C.-35° C. Humidity 10-90% non-condensing Location Normallaboratory conditions - out of direct sunlight

The present invention has now been described in connection with a numberof specific embodiments thereof. However, numerous modifications whichare contemplated as falling within the scope of the present inventionshould now be apparent to those skilled in the art. It is thereforeintended that the scope of the present invention be limited only by thescope of the claims appended hereto. In addition, the order ofpresentation of the claims should not be construed to limit the scope ofany particular term in the claims.

1. A spectroscopic apparatus for investigating heterogeneity of a samplearea, comprising: an image acquisition system operative to acquireimages of a plurality of sub-areas in the sample area, a sub-areaselection interface operative to receive a selection designating one ofthe sub-areas for which an image has been obtained, a spectrometerhaving a field of view and being operative to acquire a spectrum of atleast part of one of the sub-areas in its field of view, and apositioning mechanism responsive to the sub-area selection interface andoperative to position the field of view of the spectrometer relative tothe sample area based on a received selection.
 2. The apparatus of claim1 wherein the positioning mechanism includes electromechanical elements.3. The apparatus of claim 1 wherein the positioning mechanism includesan x-y stage responsive to x-y coordinate information from the sub-areaselection interface.
 4. The apparatus of claim 1 wherein the sub-areaselection interface is responsive to direct selection of a sub-area by auser.
 5. The apparatus of claim 1 further including analysis logicoperative to analyze the images acquired by the image acquisitionsystem.
 6. The apparatus of claim 5 wherein the sub-area selectioninterface is responsive to the analysis logic to select sub-areas havingpredetermined characteristics.
 7. The apparatus of claim 6 wherein thesub-area selection interface is responsive to the analysis logic toselect sub-areas having predetermined morphological characteristics. 8.The apparatus of claim 5 wherein the sub-area selection interface isresponsive to the analysis logic to select sub-areas havingpredetermined color characteristics.
 9. The apparatus of claim 5 whereinthe analysis logic includes statistical analysis logic.
 10. Theapparatus of claim 5 wherein the analysis logic includes sorting logic.11. The apparatus of claim 5 wherein the analysis logic includescontaminant detection logic.
 12. The apparatus of claim 1 wherein thespectrometer is an infrared spectrometer.
 13. The apparatus of claim 1wherein the spectrometer is a Raman spectrometer.
 14. The apparatus ofclaim 1 wherein the area is an area of dispersed particles and the subareas are individual particles in the area of dispersed particles. 15.The apparatus of claim 1 wherein the image acquisition system operatesin the visible range.
 16. The apparatus of claim 1 further including amapping module responsive to the image acquisition system and to thespectrometer and operative to create a map that presents spectralinformation for each of the sub-areas from the spectrometer at alocation from which it was received.
 17. The apparatus of claim 16wherein the mapping module is operative to superimpose the spectralinformation onto an image from the image acquisition system.
 18. Theapparatus of claim 16 wherein the mapping module maps point measurementvalues to larger areas having matching physical characteristics.
 19. Theapparatus of claim 16 wherein the mapping module is also operative toindicate statistical properties of mapped areas.
 20. The apparatus ofclaim 16 wherein the positioning mechanism includes electromechanicalelements.
 21. The apparatus of claim 16 wherein the positioningmechanism includes an x-y stage responsive to x-y coordinate informationfrom the sub-area selection interface.
 22. The apparatus of claim 16wherein the sub-area selection interface is responsive to directselection of a sub-area by a user.
 23. The apparatus of claim 16 furtherincluding analysis logic operative to analyze the images acquired by theimage acquisition system.
 24. The apparatus of claim 23 wherein thesub-area selection interface is responsive to the analysis logic toselect sub-areas having predetermined characteristics.
 25. The apparatusof claim 24 wherein the sub-area selection interface is responsive tothe analysis logic to select sub-areas having predeterminedmorphological characteristics.
 26. The apparatus of claim 23 wherein thesub-area selection interface is responsive to the analysis logic toselect sub-areas having predetermined color characteristics.
 27. Theapparatus of claim 23 wherein the analysis logic includes statisticalanalysis logic.
 28. The apparatus of claim 23 wherein the analysis logicincludes sorting logic.
 29. The apparatus of claim 23 wherein theanalysis logic includes contaminant detection logic.
 30. The apparatusof claim 16 wherein the spectrometer is an infrared spectrometer. 31.The apparatus of claim 16 wherein the spectrometer is a Ramanspectrometer.
 32. The apparatus of claim 16 wherein the area is an areaof dispersed particles and the sub areas are individual particles in thearea of dispersed particles.
 33. The apparatus of claim 16 wherein theimage acquisition system operates in the visible range.
 34. Aspectroscopic method for investigating heterogeneity of a sample area,comprising: acquiring images of a plurality of sub-areas in the samplearea using an image acquisition system, receiving a selection of one ofthe sub-areas for which an image has been obtained, positioning a fieldof view of a spectrometer relative to the sample area so as to place atleast part of the selected sub-area in the field of view, and acquiringa spectrum of the selected sub-area.
 35. The method of claim 34 furtherincluding the step of mapping spectral information from the spectrometerto a location from which it was received.
 36. The method of claim 34further including the steps of deriving physical information about theone of the sub-areas, and setting a spectral range of the step ofacquiring in response to the physical information.
 37. A spectroscopicapparatus for investigating heterogeneity of a sample area, comprising:means for acquiring images of a plurality of sub-areas in a sample,means for receiving a selection of one of the sub-areas for which animage has been obtained, means for positioning a field of view of aspectrometer relative to the sample area so as to place at least part ofthe selected sub-area in the field of view, and means for acquiring aspectrum of the selected sub-area.
 38. A spectroscopic method forinvestigating heterogeneity of a sample area, comprising: receivingspatial information for a plurality of sub-areas in a sample area,receiving separate spectral information items for each of the pluralityof sub areas, wherein a selection of the separate spectral informationitems is based on the spatial information, and combining the spatialinformation with the spectral information to create a map showingspatial distribution of spectral information for the sample area. 39.The method of claim 38 further including the step of acquiring thespatial information by a preliminary imaging system and the step ofacquiring the spectral information by a spectrometer that is responsiveto automatically generated identification information derived from thespatial information acquired in the step of acquiring.
 40. Aspectroscopic apparatus for investigating heterogeneity of a samplearea, comprising: means for receiving spatial information for aplurality of sub-areas in a sample area, means for receiving separatespectral information items for each of the plurality of sub areas,wherein a selection of the separate spectral information items is basedon the spatial information, and means for combining the spatialinformation with the spectral information to create a map showingspatial distribution of spectral information for the sample area.
 41. Aapparatus for investigating heterogeneity of a sample area, comprising:an image acquisition system operative to acquire images of a pluralityof sub-areas in the sample area, a sub-area selection interfaceoperative to automatically select one of the sub-areas for which animage has been obtained based on its color, and quantitative analysislogic operative to perform a quantitative analysis on image data fromone or more of the sub-areas.
 42. The apparatus of claim 41 wherein thesub-area selection interface is operative to automatically select one ofthe sub-areas for which an image has been obtained based on a color thatcorresponds to a predetermined stain.
 43. A method for investigatingheterogeneity of a sample area, comprising: acquiring images of aplurality of sub-areas in the sample area, automatically selecting oneof the sub-areas for which an image has been obtained based on itscolor, and performing a quantitative analysis on image data from one ormore of the sub-areas.
 44. An apparatus for investigating heterogeneityof a sample area, comprising: means for acquiring images of a pluralityof sub-areas in the sample area, means for automatically selecting oneof the sub-areas for which an image has been obtained based on itscolor, and means for performing a quantitative analysis on image datafrom one or more of the sub-areas.